meg-converter.py

#!/usr/bin/env python3

""" Convert MEG data to the 2vs2 CSV input file format """

import csv
import tables

file = tables.open_file('../data/meg_data_averaged.mat')

def get_word(file, word):
    return ''.join([chr(i) for i in file.root.words[0][word][0]])

with open('output.csv', 'w', newline='') as csvfile:

    num_readings = len(file.root.data)
    num_sensors = len(file.root.data[0])
    num_words = len(file.root.data[0][0])
    writer = csv.writer(csvfile)

    for _ in range(2):
        for word in range(num_words):
            for reading in range(num_readings):
                row = [ word, get_word(file, word) ]
                for sensor in range(num_sensors):
                    row.append(file.root.data[reading][sensor][word])
                row += [ 0, 0, 0 ]
                writer.writerow(row)

            average_row = length*num_sensors*[0]
            average_row2 = length*num_sensors*[0]
            if len(trial_row) == 0: continue
            B = trial_rows[:len(trial_rows)/2]
            C = trial_rows[len(trial_rows)/2:]
            for trial_row in B:
                for i, element in enumerate(trial_row):
                    average_row[i] += element
            for trial_row in C:
                for i, element in enumerate(trial_row):
                    average_row[i] += element
            size = len(group)
            size = len(group)